The method of the present invention relates generally to the accurate registration of a detected sensor located in moving lungs to a static image of the lungs. The evolution of procedures using less-invasive scopes has resulted in the development of sensors that can be attached to end of an endoscope and used to determine the three-dimensional location and orientation of the end of the endoscope. Examples of such sensor technology is shown and described in various patents and patent publications including U.S. Pat. No. 6,188,355 to Gilboa, U.S. Pat. No. 6,380,732 to Gilboa, U.S. Pat. No. 6,593,884 to Gilboa et al., U.S. Pat. No. 6,615,155 to Gilboa, U.S. Pat. No. 6,833,814 to Gilboa et al., U.S. Pat. No. 6,947,788 to Gilboa et al., each of which is incorporated herein in its entirety. Additionally, there are many other technologies (laser technology, ultrasound technology, etc.) directed toward for locating a medical tool (catheter, endoscope, needle) inside the human lungs.
One problem that arises while using these localization methods is that, in order to provide information that is useful to a physician, a display must be used that shows a representation of the tool superimposed on an image of the lungs. If a static image of the lungs is used, the tool, which is moving with the lungs as the patient breathes, appears to float in and out of the airways in the preliminary, relatively static image. Accurately matching the position of the sensor in the lungs to an image of the lungs is achieved by “registration.” Ideally, the desired result of registration would involve matching the tool representation to a real-time, dynamic image of the lungs. However, this would require constant exposure to X-ray radiation by both the patient and the medical staff during while performing the dynamic registration.
One approach at solving this problem is described in U.S. Pat. No. 7,117,026 to Shao et al., which is incorporated by reference herein in its entirety. Shao is directed to reconciling a dynamic, PET imaging data set with a static CT imaging data set. Shao accomplishes this by merely morphing (stretching or distorting) the image sets together. Doing so does not necessarily improve the accuracy of the real-time data being displayed because at least one of the data sets is being distorted. Rather, this approach merely makes the display appear to be more accurate. Moreover, PET requires prolonged exposure to radioactive imaging agents.
Another approach at solving this problem is described in U.S. Patent Publication No. 2003/0185346 to Vilsmeier. Vilsmeier is directed to avoiding costly CT scans by building a generic model of various areas of the body using a compilation of data from various patients, and then adapting that generic model to a specific patient. This idea certainly reduces costs and exposure to radiation, however it necessarily compromises image accuracy. Moreover, though the anatomy of the trachea and upper bronchial anatomy is very similar in most people, the lower bronchi become very patient-specific. It is in these lower bronchi where accurate information is most important. Finally, Vilsmeier does not address developing a dynamic model. Not only are the lower bronchi more patient-specific, they move more. So even if one where to use the Vilsmeier model to create a dynamic lung simulation, the lack of accuracy in the lower bronchi would not solve the problem the present invention addresses.
One reference that discusses the development of a generic model and begins to analyze the movement vectors for a breathing cycle is entitled “Development of a Dynamic Model for the Lung Lobes and Airway Tree in the NCAT Phantom” and is written by Garrity et al. This reference was published in 2002 as part of the Nuclear Science Symposium Conference Record, and appears in IEEE Vol. 3, pp. 1858-1862. This reference is incorporated herein in its entirety. It describes an algorithm that fills an empty outline of a simulated lung lobe with a virtual bronchial tree. The bronchial tree simulates movement due to breathing and cardiac rhythms. Because the model is completely simulated, it is useful for studying lung movement and the effects of tumor, but it would not have application during a procedure on an actual patient. Additionally, the reference discusses movement vectors within the lungs, but it does not find a mathematical relationship between these various vectors.
There is thus an identified need for a representation of the lungs that is more representative of a breathing patient's lungs than a static, previously acquired image, but does not result in an increased exposure to radiation.